面向学习分析的机器学习和大数据方法

Prasanth Sai Gouripeddi, R. Gouripeddi, Sai Preeti Gouripeddi
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引用次数: 2

摘要

由于在线学习方法和虚拟学习环境的出现,教育模式发生了转变。机器学习方法以前在有限的情况下用于学习分析。这些模型可以预测学习结果,并使人们能够理解各种学习变量之间的关系。这种预测所需的数据通常是复杂的,有多种关系。在本文中,我们在开放大学学习分析数据集上使用支持向量回归和图表示,以提供使用机器学习方法和图数据库创建预测模型以改进学习方法的视图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toward Machine Learning and Big Data Approaches for Learning Analytics
There is a paradigm shift in education due to online learning approaches and virtual learning environments. Machine learning methods have been used in a limited manner previously for learning analytics. These models can predict learning outcomes and enable understanding relationships between various learning variables. The data required for such predictions are usually complex with multiple relationships. In this paper, we use Support Vector Regression and Graph representation on the Open University Learning Analytics Dataset to provide a view into the use of machine learning methods and graph databases in creating predictive models for bettering the learning approaches.
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